Apr 23 at 12pm (NSH 3305) -- Yexiang Xue (Purdue) -- Vertical Reasoning Enhanced Learning, Generation and Scientific Discovery

[Victor Akinwande]

Quick reminder that this talk is happening later today at NSH 3305.

See you there!

On Wed, Apr 17, 2024 at 12:27 PM Victor Akinwande <vakinwan at andrew.cmu.edu>
wrote:

> Dear all,
>
> We look forward to seeing you next Tuesday (04/23) from 12:00-1:00 PM (ET)
> for the next talk of this semester's CMU AI Seminar, sponsored by SambaNova
> Systems (https://sambanova.ai). The seminar will be held in NSH 3305 with
> pizza provided and will be streamed on Zoom.
>
> To learn more about the seminar series or to see the future schedule,
> please visit the seminar website (http://www.cs.cmu.edu/~aiseminar/).
>
> Next Tuesday (04/23),  Yexiang Xue (Purdue) will be giving a talk titled
> "Vertical Reasoning Enhanced Learning, Generation and Scientific Discovery".
>
> ///////////////////
> *Talk Abstract: *
> Automated reasoning and machine learning are two fundamental pillars of
> artificial intelligence. Despite much recent progress, the full integration
> of reasoning and learning is beyond reach. This talk presents three cases
> where integrated vertical reasoning significantly enhances learning. Our
> first case is in neural generation, where state-of-the-art models struggle
> to generate pleasing images while satisfying complex specifications. We
> introduce Spatial Reasoning INtegrated Generator (SPRING). SPRING embeds a
> spatial reasoning module inside the deep generative network to reason
> object locations. This embedded approach guarantees constraint
> satisfaction, offers interpretability, and facilitates zero-shot transfer
> learning. Our second case is in AI-driven scientific discovery, where we
> embed vertical reasoning to expedite symbolic regression. Vertical
> reasoning builds from reduced models that involve a subset of variables (or
> processes) to full models, inspired by the human scientific approach.
> Vertical discovery outperforms horizontal ones at discovering equations
> involving many variables and complex processes, especially in learning PDEs
> in computational materials science. In the third case, we demonstrate that
> vertical reasoning enables constant approximation guarantees in solving
> Satisfiable Modulo Counting (SMC). SMC involves model counting as
> predicates in Boolean satisfiability. It encompasses many problems that
> require both symbolic decision-making and statistical reasoning, e.g.,
> stochastic optimization, hypothesis testing, solving quantal-response
> leader-follower games, and learning (inverse reinforcement learning) with
> provable guarantees. Using vertical reasoning that streamlines XOR
> constraints, our proposed XOR-SMC reduces highly intractable SMC problems
> into solving satisfiability instances, while obtaining a constant
> approximation guarantee.
>
>
> *Speaker Bio: *Dr. Yexiang Xue is an assistant professor in the
> Department of Computer Science, Purdue University. The goal of Dr. Xue’s
> research is to bridge large-scale constraint-based reasoning with
> state-of-the-art machine learning techniques to enable intelligent agents
> to make optimal decisions in high-dimensional and uncertain real-world
> applications. More specifically, Dr Xue’s research focuses on scalable and
> accurate probabilistic reasoning, statistical modeling of data, and robust
> decision-making under uncertainty. His work is motivated by key problems
> across multiple scientific domains, ranging from artificial intelligence,
> machine learning, renewable energy, materials science, crowdsourcing,
> citizen science, urban computing, ecology, to behavioral econometrics. Dr.
> Xue obtained his PhD from Cornell, supervised by Professor Bart Selman and
> Professor Carla Gomes, before joining Purdue in 2018. Recently, Dr. Xue has
> been focusing on developing cross-cutting computational methods, with an
> emphasis in the areas of computational sustainability and AI-driven
> scientific discovery.
> ///////////////////
>
> *In person: NSH 3305*
> *Zoom Link:
>  https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09
> <https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09>*
>
>
> - Victor & Asher
>
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